[HTML][HTML] An in-depth review of machine learning based Android malware detection

A Muzaffar, HR Hassen, MA Lones, H Zantout - Computers & Security, 2022 - Elsevier
It is estimated that around 70% of mobile phone users have an Android device. Due to this
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …

A survey of android application and malware hardening

V Sihag, M Vardhan, P Singh - Computer Science Review, 2021 - Elsevier
In the age of increasing mobile and smart connectivity, malware poses an ever evolving
threat to individuals, societies and nations. Anti-malware companies are often the first and …

Deep feature extraction and classification of android malware images

J Singh, D Thakur, F Ali, T Gera, KS Kwak - Sensors, 2020 - mdpi.com
The Android operating system has gained popularity and evolved rapidly since the previous
decade. Traditional approaches such as static and dynamic malware identification …

Malicious application detection in android—a systematic literature review

T Sharma, D Rattan - Computer Science Review, 2021 - Elsevier
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …

Constructing features for detecting android malicious applications: issues, taxonomy and directions

W Wang, M Zhao, Z Gao, G Xu, H Xian, Y Li… - IEEE …, 2019 - ieeexplore.ieee.org
The number of applications (apps) available for smart devices or Android based IoT (Internet
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …

Obfuscation-resilient android malware analysis based on complementary features

C Gao, M Cai, S Yin, G Huang, H Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Existing Android malware detection methods are usually hard to simultaneously resist
various obfuscation techniques. Therefore, bytecode-based code obfuscation becomes an …

Sharing more and checking less: Leveraging common input keywords to detect bugs in embedded systems

L Chen, Y Wang, Q Cai, Y Zhan, H Hu… - 30th USENIX Security …, 2021 - usenix.org
IoT devices have brought invaluable convenience to our daily life. However, their
pervasiveness also amplifies the impact of security vulnerabilities. Many popular …

[HTML][HTML] Android application forensics: A survey of obfuscation, obfuscation detection and deobfuscation techniques and their impact on investigations

X Zhang, F Breitinger, E Luechinger… - Forensic Science …, 2021 - Elsevier
Android obfuscation techniques include not only classic code obfuscation techniques that
were adapted to Android, but also obfuscation methods that target the Android platform …

A survey and evaluation of android-based malware evasion techniques and detection frameworks

P Faruki, R Bhan, V Jain, S Bhatia, N El Madhoun… - Information, 2023 - mdpi.com
Android platform security is an active area of research where malware detection techniques
continuously evolve to identify novel malware and improve the timely and accurate detection …

The rise of obfuscated Android malware and impacts on detection methods

WF Elsersy, A Feizollah, NB Anuar - PeerJ Computer Science, 2022 - peerj.com
The various application markets are facing an exponential growth of Android malware. Every
day, thousands of new Android malware applications emerge. Android malware hackers …